In recent years, genetic information has become increasingly available through research efforts such as the Human Genome Project. However, genetic information has not been incorporated effectively into the clinical decision making process. Genetic specialists have been among the first to incorporate this new information into their practice. However, non-specialists, such as general practitioners, pediatricians, surgeons and pharmacists, also need to improve their practices to reflect recent advances in genetics research even though they may lack a deep understanding of genetics.
As more genetic information has become available, technical advances have led to affordable genetic testing for many relevant genetic mutations. Nonetheless, most individuals have not undergone genetic testing and widespread use of genetic testing is likely to take five to ten years. Thus, for an individual patient, result values for mutations in a particular gene relevant to that patient's treatment may not always be available. However, genetic findings for one or more family members of the individual may be available. Demographic information and genetic findings for linked genes may also be available. While this information can be used to infer a genetic test result, it has not yet been integrated into an effective clinical process for the non-expert to use in the clinical decision making process.
Existing programs for inferring genetic finds are ineffective for a number of reasons. These programs require a user actively to solicit an inference. Once the user deliberately launches one of the existing programs, the program requires the user to complete a family tree by asking the user to indicate medical conditions known for each individual in the family tree. The user then selects an individual(s) in the family tree and the program returns a prediction. Thus, in these programs, the user must launch the program and specifically request a prediction for a particular person. Since the programs are not integrated into a unified healthcare information technology system, information about a person's family must be input manually. While the relationships are relatively simple, the genetic information is oftentimes difficult to understand and input into the system. As such, these programs are used by individuals with significant training and expertise in genetics. Even with skilled operators, the opportunities for human error are significant and the consequences of such errors is oftentimes great.
Accordingly, there is a need for an effective system and method for incorporating genetic information about the family of a patient into the clinical decision making process for the beneficial use by the non-expert. A need also exists for a system capable of inferring genetic findings for a patient when such a result would be useful in the decision making process but is absent for the patient being treated. Still another need is for a system that infers genetic findings for an individual in a reliable, cost effective, efficient and safe manner.